| Literature DB >> 31181068 |
Adam Bonica1, Howard Rosenthal2, David J Rothman3.
Abstract
Although a substantial literature considers physician advocacy fundamental to medical professionalism, only a minority of physicians actually pursue it. We analyze the characteristics of 6,402 physicians who engaged in political advocacy by signing the Clinician Action Network's 2016 petition objecting to the American Medical Association's endorsement of the nomination of Tom Price as Secretary of Health and Human Services. These physicians were matched to the NPI (all physicians) and PECOS (largely Medicare payment recipients) directories. Physicians in the directories were matched to publicly disclosed campaign contributions. Contributions are used to measure political preferences expressed on a liberal-conservative scale. We document a pronounced generational realignment in the politics of the medical profession, with recent graduates trending sharply Democratic. Petition signing vs. non-signing is responsive to gender, specialty, geographic location, personal liberal-conservative preferences and year of graduation from medical school. Petition signers were more likely to be women (62% of signers versus 34% of non-signers), recent medical school graduates (58% of signers versus 42% of non-signers), and in lower-paying specialties (27% of signers versus 12% of non-signers). The changing face of physician advocacy has important implications for understanding how the medical profession is likely to influence health care policy in coming decades.Entities:
Mesh:
Year: 2019 PMID: 31181068 PMCID: PMC6557476 DOI: 10.1371/journal.pone.0215802
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Percentage of campaign contributions to Republicans by year of medical school graduation and gender.
Source: NPPES Downloadable File and DIME. Authors’ calculations.
Fig 2Party registration of Florida physicians by year of medical school graduation.
Source: NPPES Downloadable File, Florida Secretary of State, and DIME.
Fig 3Ideological distributions of physicians.
Source: Authors calculations. Data on candidates and physician DIME score are from DIME (Bonica 2016). Note: To aid in interpreting the scale, ideal points for several well-known presidential candidates are shown at the bottom of the figure.
Effect of ideology, sex, location, specialty, cohort: Logit dependent variable, signed the petition.
| Model 1 | Model 2 | Model 3 | |
|---|---|---|---|
| (Intercept) | -6.076 | -6.002 | -90.174 |
| (0.054) | (0.061) | (715.918) | |
| Physician DIME score | -1.463 | -1.457 | -1.060 |
| (0.039) | (0.044) | (0.048) | |
| Female | 0.684 | ||
| (0.065) | |||
| Zip3 DIME score | -0.989 | ||
| (0.082) | |||
| Graduation Year | 0.035 | ||
| (0.003) | |||
| Specialty FEs | No | No | Yes |
| AIC | 16520.79 | 11746.89 | 11091.10 |
| Log Likelihood | -8258.40 | -5871.45 | -5449.55 |
| Num. obs. | 241,236 | 174,359 | 174,359 |
Note: Fixed effects for 92 specialties not shown.
Effects of contributing in 2015–16 election cycle, sex, and cohort: Logit dependent variable, signed the petition.
| Model 1 | Model 2 | Model 3 | |
|---|---|---|---|
| (Intercept) | -5.671 | -5.634 | -99.376 |
| (0.018) | (0.021) | (255.085) | |
| Contributed | 1.361 | 1.271 | 1.644 |
| (0.039) | (0.047) | (0.049) | |
| Female | 0.831 | ||
| (0.042) | |||
| Zip3 DIME score | -1.479 | ||
| (0.050) | |||
| Graduation Year | 0.040 | ||
| (0.002) | |||
| Specialty FEs | No | No | Yes |
| AIC | 51926.545 | 36204.144 | 32897.716 |
| Log Likelihood | -25961.272 | -18100.072 | -16352.858 |
| Num. obs. | 1,001,467 | 680,518 | 680,518 |
Note: Fixed effects for 92 specialties not shown.
Effects of signing petition, donor status, sex, and cohort: Logit dependent variable, contributing within 3, 6, and 12 months of petition.
| Model 1 | Model 2 | Model 3 | |
|---|---|---|---|
| (Intercept) | 58.188 | 58.008 | 59.950 |
| (2.098) | (1.588) | (1.370) | |
| Signed Petition | 1.119 | 1.125 | 1.128 |
| (0.096) | (0.081) | (0.075) | |
| Contributed in 2016 | 3.115 | 3.026 | 2.976 |
| (0.026) | (0.019) | (0.016) | |
| Graduation Year | -0.032 | -0.032 | -0.032 |
| (0.001) | (0.001) | (0.001) | |
| Female | 0.099 | 0.033 | -0.007 |
| (0.031) | (0.024) | (0.021) | |
| Zip3 DIME score | -0.178 | -0.100 | -0.059 |
| (0.031) | (0.023) | (0.020) | |
| Specialty FEs | Yes | Yes | Yes |
| AIC | 62056.073 | 99776.074 | 128563.049 |
| Log Likelihood | -30931.036 | -49791.037 | -64184.524 |
| Num. obs. | 680,518 | 680,518 | 680,518 |
Note: Fixed effects for 92 specialties not shown.